KR20160017941A - Method and apparatus for authenticating user using fingerprint and ecg signal - Google Patents

Method and apparatus for authenticating user using fingerprint and ecg signal Download PDF

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KR20160017941A
KR20160017941A KR1020140101660A KR20140101660A KR20160017941A KR 20160017941 A KR20160017941 A KR 20160017941A KR 1020140101660 A KR1020140101660 A KR 1020140101660A KR 20140101660 A KR20140101660 A KR 20140101660A KR 20160017941 A KR20160017941 A KR 20160017941A
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South Korea
Prior art keywords
similarity
user
degree
humidity level
fingerprint
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KR1020140101660A
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Korean (ko)
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배치성
김상준
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삼성전자주식회사
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Priority to KR1020140101660A priority Critical patent/KR20160017941A/en
Publication of KR20160017941A publication Critical patent/KR20160017941A/en

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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00006Acquiring or recognising fingerprints or palmprints
    • G06K9/00067Preprocessing; Feature extraction (minutiae)
    • G06K9/0008Extracting features related to ridge properties; determining the fingerprint type, e.g. whorl, loop
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00006Acquiring or recognising fingerprints or palmprints
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00006Acquiring or recognising fingerprints or palmprints
    • G06K9/00013Image acquisition
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00006Acquiring or recognising fingerprints or palmprints
    • G06K9/00013Image acquisition
    • G06K9/0002Image acquisition by non-optical methods, e.g. by ultrasonic or capacitive sensing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00006Acquiring or recognising fingerprints or palmprints
    • G06K9/00087Matching; Classification
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00885Biometric patterns not provided for under G06K9/00006, G06K9/00154, G06K9/00335, G06K9/00362, G06K9/00597; Biometric specific functions not specific to the kind of biometric
    • G06K9/00892Use of multiple biometrics
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6288Fusion techniques, i.e. combining data from various sources, e.g. sensor fusion
    • G06K9/6289Fusion techniques, i.e. combining data from various sources, e.g. sensor fusion of input or preprocessed data
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00885Biometric patterns not provided for under G06K9/00006, G06K9/00154, G06K9/00335, G06K9/00362, G06K9/00597; Biometric specific functions not specific to the kind of biometric
    • G06K2009/00939Biometric patterns based on physiological signals, e.g. heartbeat, blood flow

Abstract

Disclosed are a method and an apparatus for authenticating a user using a fingerprint and an electrocardiogram (EEG) signal. The authenticating apparatus obtains the fingerprint information and EEG waveform of a user, obtains the humidity level of the skin of the user, adaptively controls a first similarity which indicates similarity between a reference fingerprint and a fingerprint information, and a second similarity which indicates similarity between a reference EEG waveform and an EEG waveform, based on the humidity level, extracts mixture similarity, and authenticates whether the user is a registered user by using the mixture similarity.

Description

TECHNICAL FIELD [0001] The present invention relates to a fingerprint authentication device, a fingerprint authentication device, and an electrocardiogram signal authentication device,

The following embodiments relate to a user authentication method and apparatus using fingerprint and electrocardiogram signals.

Techniques using various signals and data that can be extracted from a living body and using them in various systems are being developed. In particular, biometrics technology that constructs a security system using biometric signals or data is getting popular. Biometrics technology refers to a technology that extracts signals and data related to a living body from a user, compares it with previously stored data, verifies the identity of the user, and authenticates the user. For example, as one of the fields of biometrics technology, a technique of recognizing a user by using an electrocardiogram (ECG) signal is being developed.

Since biometrics technology utilizes the individual's own bio-signals, there is no fear of theft or loss, and it is becoming popular in the security field because it is difficult to forge or tamper with. Recently, studies for increasing the recognition rate of an individual's own bio-signal are continuing.

An authentication apparatus according to an embodiment includes a biometric information obtaining unit that obtains fingerprint information and electrocardiogram waveform of a user; A humidity level obtaining unit for obtaining a humidity level of the skin of the user; A first degree of similarity between the reference fingerprint information and the fingerprint information and a second degree of similarity between the reference ECG waveform and the ECG waveform, A degree of similarity extracting unit for extracting a degree of similarity indicating whether or not the user matches a pre-registered user corresponding to the electrocardiogram waveform; And an authentication unit for authenticating whether the user is the pre-registered user using the mixed similarity.

Wherein the biometric information obtaining unit includes a fingerprint feature point extracting unit that senses the fingerprint information using a fingerprint sensor and extracts a plurality of fingerprint feature points of the fingerprint information; And an ECG feature point extracting unit for extracting the ECG waveform using the ECG sensor and extracting a plurality of ECG feature points of the ECG waveform.

The electrocardiograph sensor includes: a plurality of electrodes for acquiring an electrocardiogram signal of the user; An amplifier for amplifying the electrocardiogram signal; And a digital converter for converting the amplified electrocardiogram signal into a digital signal and extracting the electrocardiogram waveform.

The fingerprint information, the electrocardiographic waveform and the humidity level may be obtained from the same finger of the user.

Wherein the degree of similarity extraction unit is configured to calculate the degree of similarity using the difference value between the first similarity degree and the first threshold value determined by the humidity level and the difference value between the second similarity degree and the second threshold value determined by the humidity level, It is possible to extract the mixed similarity.

The similarity extraction unit may extract the first threshold value and the second threshold value from predetermined reference information.

The similarity degree extracting unit may calculate the similarity using a difference between the number of the plurality of fingerprint feature points of each of a plurality of fingerprint information stored in advance according to the humidity level or a difference between distances between a plurality of fingerprint feature points of each of the plurality of fingerprint information items according to the humidity level The first threshold value can be extracted.

The similarity extractor may calculate a signal-to-noise ratio (SNR) of each of a plurality of electrocardiogram signals previously stored according to the humidity level, and extract the second threshold value using the SNR .

Wherein the degree of similarity extraction unit applies a first weight determined by the humidity level to a difference value between the first similarity and the first threshold value and applies the first weight to the difference value between the second similarity degree and the second threshold value, The second similarity degree determined by the humidity level can be applied to extract the similarity degree.

Wherein the similarity degree extraction unit is configured to calculate a degree of similarity by summing a difference value between the first similarity degree applied with the first weight value and the first threshold value and a difference value between the second similarity degree applied with the second weight value and the second threshold value, The degree of similarity can be calculated.

Wherein the degree of similarity extraction unit is configured to calculate the degree of similarity based on the degree of similarity when the first weight has a negative correlation with the humidity level and the second weight has a positive correlation with the humidity level, The first weight and the second weight can be set to be constant irrespective of the humidity level.

The authentication unit may authenticate the user as the pre-registered user when the degree of mixture similarity is larger than a predetermined threshold mixture value.

The plurality of fingerprint feature points may include at least two of a ridge of the fingerprint information, an upper center point, a lower center point, a left delta, a right delta, a divergence point, or a disadvantage.

The plurality of electrocardiographic characteristic points may include at least one of a PR segment, a QRS complex, an ST segment, a T wave, a U wave, a PR interval PR interval) or a QT interval (QT interval).

An authentication apparatus according to an embodiment includes a fingerprint sensor that senses fingerprint information of a user; An electrocardiogram sensor for sensing the electrocardiogram waveform of the user using the first electrode, the second electrode, and the third electrode; A humidity sensor for sensing the humidity level of the user's skin; And a second degree of similarity between the reference fingerprint information and the fingerprint information and adaptively adjusting a second degree of similarity between the reference ECG waveform and the ECG waveform based on the humidity level, And a processor for extracting a mixed similarity degree indicating whether the user matches the pre-registered user corresponding to the reference ECG waveform and authenticating whether the user is the pre-registered user using the mixed similarity degree .

The first electrode, the fingerprint sensor, and the humidity sensor may be located within a predetermined area.

The first electrode, the fingerprint sensor and the humidity sensor may sense the same finger of the user.

Wherein the processor is configured to calculate a difference between the first degree of similarity and a first threshold value determined by the humidity level and a difference value between the second degree of similarity and a second threshold value determined by the humidity level, The degree of similarity can be extracted.

Wherein the processor applies a first weight determined by the humidity level to a difference between the first degree of similarity and the first threshold and applies the difference to the difference between the second degree of similarity and the second threshold, The second similarity degree can be extracted by applying a second weight determined by the level.

Wherein the processor is configured to combine a difference value between the first similarity degree applied with the first weight value and the first threshold value and a difference value between the second similarity degree applied with the second weight value and the second threshold value, Can be calculated.

An authentication apparatus according to an embodiment includes a biometric information obtaining unit that obtains a plurality of biometric information of a user; A humidity level obtaining unit for obtaining a humidity level of the skin of the user; The individual similarity degree indicating the degree of similarity between each of the plurality of pieces of the biometric information and the reference biometric information corresponding to each of the plurality of pieces of the biometric information among the plurality of pieces of the reference biometric information is adaptively adjusted based on the humidity level, A degree of similarity extracting unit for extracting a degree of similarity indicating whether or not the user matches a user registered in advance corresponding to the information; And an authentication unit for authenticating whether the user is the pre-registered user using the mixed similarity.

An authentication method according to an exemplary embodiment includes: obtaining fingerprint information of a user and an electrocardiogram waveform; Obtaining a humidity level of the skin of the user; Calculating a first degree of similarity between the reference fingerprint information and the fingerprint information and a second degree of similarity between the reference ECG waveform and the ECG waveform; Wherein the first degree of similarity and the second degree of similarity are adaptively adjusted on the basis of the humidity level so that a mixed similarity degree indicating whether or not the user is in agreement with a previously registered user corresponding to the reference fingerprint information and the reference ECG waveform Extracting; And authenticating whether the user is the pre-registered user using the mixed similarity.

An authentication method according to an exemplary embodiment includes: acquiring a plurality of biometric information of a user; Obtaining a humidity level of the skin of the user; Calculating individual degree of similarity of each of the plurality of pieces of biometric information and each of the plurality of pieces of biometric information indicating a degree of similarity between reference biometric information corresponding to each of the plurality of pieces of biometric information among a plurality of pieces of reference biometric information; Extracting a mixed similarity degree indicating whether or not the user is in agreement with a previously registered user corresponding to the plurality of biometric information by adaptively adjusting an individual similarity degree of each of the plurality of biometric information on the basis of the humidity level; And authenticating whether the user is the pre-registered user using the mixed similarity.

1 is a block diagram showing an authentication apparatus according to an embodiment.
2 is a diagram for explaining quality of fingerprint information and electrocardiographic waveform according to a humidity level according to an embodiment.
FIG. 3 is a diagram for explaining threshold values of a first similarity degree and a second similarity degree according to a humidity level according to an embodiment.
4 is a view for explaining a lookup table including information according to a humidity level according to an embodiment.
5 is a block diagram showing an authentication apparatus according to another embodiment.
6 is a diagram for explaining an example of an authentication apparatus according to an embodiment.
7 is a diagram for explaining an example of an authentication apparatus according to another embodiment.
8 is a diagram for explaining an example of an authentication apparatus according to another embodiment.
9 is a flowchart illustrating an authentication method according to an embodiment.
10 is an operation flowchart showing an authentication method according to another embodiment.

In the following, embodiments will be described in detail with reference to the accompanying drawings. Like reference symbols in the drawings denote like elements.

Various modifications may be made to the embodiments described below. It is to be understood that the embodiments described below are not intended to limit the embodiments, but include all modifications, equivalents, and alternatives to them.

The terms used in the examples are used only to illustrate specific embodiments and are not intended to limit the embodiments. The singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, the terms "comprises" or "having" and the like refer to the presence of stated features, integers, steps, operations, elements, components, or combinations thereof, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this embodiment belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Do not.

In the following description of the present invention with reference to the accompanying drawings, the same components are denoted by the same reference numerals regardless of the reference numerals, and redundant explanations thereof will be omitted. In the following description of the embodiments, a detailed description of related arts will be omitted if it is determined that the gist of the embodiments may be unnecessarily blurred.

1 is a block diagram showing an authentication apparatus according to an embodiment.

Referring to FIG. 1, the authentication device 110 may include a biometric information obtaining unit 120, a humidity level obtaining unit 130, a similarity extracting unit 140, and an authentication unit 150.

The biometric information obtaining unit 120 can obtain a plurality of biometric information of the user. The authentication device 110 can determine whether or not the user can access the device provided with the authentication device 120 by using the plurality of biometric information acquired by the biometric information acquisition device 120. [ The security of the authentication device 110 can be improved by the authentication device 110 authenticating the user by using a plurality of biometric information rather than one biometric information.

In one embodiment, the biometric information acquiring unit 120 acquires the biometric information of the user, such as fingerprint information, electrocardiogram (ECG) information, electromyography (EMG) information, iris information, blood vessel information, vein information, Information and the like from the corresponding sensor. In one embodiment, the biometric information obtaining unit 120 may obtain a plurality of biometric information affected by the humidity level. Hereinafter, the authentication apparatus 110 will be described focusing on fingerprint information and electrocardiographic information among a plurality of pieces of biometric information. Biometric information used by the authentication device 110 is not limited to fingerprint information and electrocardiographic information.

The biometric information obtaining unit 120 may include a fingerprint feature point extracting unit and an electrocardiogram feature point extracting unit. The fingerprint characteristic point extracting unit can sense the fingerprint information using the fingerprint sensor. The fingerprint sensor may include an optical sensor, a semiconductor device sensor, an ultrasonic sensor, a thermal sensor, a non-contact sensor, or a hybrid sensor. The fingerprint feature point extracting unit can extract a plurality of fingerprint feature points of the fingerprint information. Here, the plurality of fingerprint feature points may include at least two of a fingerprint ridge, an upper center point, a lower center point, a left delta, a right delta, a divergence point, or a disadvantage. The fingerprint minutiae extracting unit can distinguish between dark and light fingerprint information received from the fingerprint sensor and remove noise. For example, the fingerprint characteristic point extraction unit extracts direction components of each ridge of the fingerprint information, separates the ridge and the bone, binarizes the ridge and the bone, and determines the thickness of each ridge to thin the line. Further, in one embodiment, the fingerprint feature point extracting unit extracts ridges from the thinned fingerprint information, and extracts ridges from the thinned fingerprint information and extracts ridges based on the ridges of the upper center point, the lower center point, the left delta lug, the right delta lug, And the like can be extracted.

The ECG feature extraction unit can extract an ECG waveform using an ECG sensor. The ECG sensor may include a plurality of electrodes, an amplifier, and a digital converter. The plurality of electrodes can contact the user's skin (e.g., a finger) to sense the electrocardiogram signal of the user. The amplifier can amplify the sensed electrocardiogram signal at a plurality of electrodes. In one embodiment, the amplifier may be represented by an analog front end (AFE). Digital converter converts an amplified electrocardiogram signal into a digital signal to extract an electrocardiogram waveform. Accordingly, the signal-to-noise ratio (SNR) of the electrocardiogram signal can be improved. In addition, the ECG feature point extraction unit can remove the noise of the ECG waveform through the preprocessing process. In addition, the ECG feature point extracting unit may extract a plurality of ECG feature points from the ECG signal received from the ECG sensor. Here, the ECG feature point is a PR segment, a QRS complex, an ST segment, a T wave, a U wave, a PR interval (PR interval), or a PR segment of an electrocardiographic waveform And a QT interval (QT interval).

The humidity level acquiring unit 130 can acquire the humidity level of the user's skin using the humidity sensor. The humidity sensor senses the amount of moisture evaporating from the user's skin and converts it into a humidity level. For example, the humidity sensor can extract a humidity level by using a change in electric resistance or capacitance caused by absorption of moisture of the skin into porous ceramics or a polymer membrane. The humidity sensor may include any sensor capable of sensing the humidity level of the skin. In one embodiment, the humidity sensor may be located near the fingerprint sensor and the wettability sensor. In this case, the humidity sensor, the fingerprint sensor, and the electrocardiogram sensor can respectively acquire the corresponding information from the same finger of the user.

The similarity extraction unit 140 may adaptively adjust the first similarity degree and the second similarity degree based on the humidity level to extract the mixed similarity degree. Here, the first degree of similarity may represent the degree of similarity between the reference fingerprint information and the fingerprint information obtained by the biometric information obtaining unit 120, and the second degree of similarity may be the degree of similarity between the reference ECG waveform and the electrocardiogram waveform obtained by the biometric information obtaining unit 120 The degree of similarity can be expressed. The reference fingerprint information and the reference ECG waveform may refer to the fingerprint information of the user registered in advance in the authentication device 110 and the electrocardiogram waveform. Here, the similarity degree of similarity may indicate whether the user who is trying to authenticate with the previously registered user corresponding to the reference fingerprint information and the reference ECG waveform is in agreement.

In one embodiment, the authentication device 110 may acquire the fingerprint information and the electrocardiographic waveform of the user who tries to authenticate in advance and store it. Also, the authentication device 110 can receive the fingerprint information of the user registered in advance from the external device and the electrocardiogram waveform.

The similarity extraction unit 140 may extract the first similarity by determining whether a plurality of fingerprint minutiae points of the fingerprint information acquired by the biometric information acquisition unit 120 and a plurality of fingerprint minutiae points of the reference fingerprint information coincide with each other. In one embodiment, the similarity extraction unit 140 may determine the first similarity using a simple pattern matching technique, a statistical identification technique, and a structural identification technique. Here, the simple pattern matching method is a technique for determining similarity by comparing whether a plurality of fingerprint minutiae points of the fingerprint information acquired by the biometric information acquisition unit 120 and extraction patterns of a plurality of fingerprint minutiae points of the reference fingerprint information are the same, The statistical identification method determines the degree of similarity by calculating the coincidence probability between the feature vector of the fingerprint information acquired by the biometric information acquisition unit 120 and the feature vector of the reference fingerprint information when direct combination of the two fingerprint feature points to be combined is impossible The structural identification technique structurally analyzes a plurality of fingerprint minutiae points of the fingerprint information and the plurality of fingerprint minutiae points of the reference fingerprint information acquired by the biometric information acquiring unit 120 and extracts the similarity from the graph It can mean a method.

The similarity extraction unit 140 may extract the second similarity using a distance between a plurality of ECG feature points of the ECG waveform acquired by the biological information acquisition unit 120 and a plurality of ECG feature points of the reference ECG waveform. In one embodiment, the similarity extraction unit 140 extracts the similarity between a plurality of electrocardiographic feature points of the electrocardiogram waveform acquired by the biometric information acquisition unit 120 and a plurality of electrocardiographic feature points of the reference electrocardiogram waveform corresponding to the euclidean norm ), The L1 similarity, the P-norm, the correlation coefficient, the root mean square error (RMSE), or the cosine similarity. The first similarity degree and the second similarity degree may increase as the fingerprint information and the electrocardiogram waveform acquired by the biometric information acquisition unit 120 are similar to the reference fingerprint information and the reference ECG waveform.

The fingerprint information acquired by the biological information acquiring unit 120 and the quality of the electrocardiogram waveform may vary depending on the humidity level. In the case of fingerprint information, when there is moisture in the user's finger contacting the fingerprint sensor, the fingerprint sensor may not correctly recognize the fingerprint feature points of the fingerprint information due to the moisture of the finger. For example, as the skin impedance of the finger in contact with the fingerprint sensor by the moisture of the finger is reduced, the fingerprint sensor may not be able to recognize the fingerprint correctly. Accordingly, when the humidity level of the finger is high, the biometric information acquiring unit 120 can acquire low quality fingerprint information, and when the humidity level of the finger is low, the biometric information acquiring unit 120 acquires high- Information can be obtained.

As another example, in the case of electrocardiographic waveforms, when moisture is present in the skin of the user contacting the electrocardiographic sensor, microcurrent between the electrode of the electrocardiographic sensor and the skin of the user may flow more easily, The quality of the electrocardiogram signal may be high. Therefore, when the humidity level of the finger is high, the biological information acquiring unit 120 can acquire a high-quality electrocardiogram waveform. When the humidity level of the finger is low, the biological information acquiring unit 120 acquires a low- Can be obtained.

In this way, the similarity extraction unit 140 can adaptively adjust the first similarity and the second similarity in consideration of the characteristic that the quality of the fingerprint information and the electrocardiogram waveform is varied by the humidity level. In one embodiment, the similarity extraction unit 140 may extract the similarity degree by applying a first threshold value and a second threshold value, which are determined by the humidity level, to the first similarity degree and the second similarity degree. Also, in another embodiment, the similarity extraction unit 140 may apply the first weight and the second weight together with the first threshold value and the second threshold value to the first similarity degree and the second similarity degree to extract the mixed similarity degree. have. For example, the similarity extraction unit 140 may extract the similarity degree by using the following equation (1).

[Equation 1]

Figure pat00001

here,

Figure pat00002
Lt; / RTI > represents the degree of hybridization,
Figure pat00003
Represents a first weight,
Figure pat00004
Represents a second weight,
Figure pat00005
Represents a first degree of similarity,
Figure pat00006
Represents a second degree of similarity,
Figure pat00007
Represents a first threshold value,
Figure pat00008
Represents a second threshold value,
Figure pat00009
May represent a ramp function. The similarity extraction unit 140 may apply the first weight to the difference between the first similarity and the first threshold and apply the second weight to the difference between the second similarity and the second threshold. At this time,
Figure pat00010
The difference value between the first similarity degree and the first threshold value may be 0 when the first similarity degree is equal to or less than the first threshold value. The similarity extraction unit 140 extracts the similarity degree by summing the difference value between the first similarity degree and the first threshold value applied with the first weight value and the difference value between the second similarity degree and the second threshold value using the second weight value. can do.

In one embodiment, the similarity extraction unit 140 may extract a first threshold value and a second threshold value from predetermined reference information. For example, the similarity extraction unit 140 may include a lookup table storing information on a first threshold value, a second threshold value, a first weight value, and a second weight value according to a humidity level. At this time, the similarity extraction unit 140 may calculate information on the first threshold value, the second threshold value, the first weight value, and the second weight value according to the humidity level in advance and store the information in the lookup table, An entry value (e.g., a first threshold value, a second threshold value, a first weight value, and a second weight value according to the humidity level) of the lookup table or the lookup table may be received from the external apparatus. The similarity extraction unit 140 may set the first threshold value, the second threshold value, the first weight value, and the second weight value by referring to the entry values of the lookup table or the lookup table.

In another embodiment, the similarity extraction unit 140 extracts the similarity between a plurality of fingerprint feature points of a plurality of fingerprint information stored in advance according to a humidity level or a difference between a plurality of fingerprint feature points of a plurality of fingerprint information points The first threshold value can be extracted using the difference between the first threshold value and the second threshold value. The number of the plurality of fingerprint feature points of the fingerprint information and the distance between the plurality of fingerprint feature points may be different depending on the humidity level. For example, the number of the plurality of fingerprint characteristic points when the humidity level is high is lower than that when the humidity level is low, and the distance between the plurality of fingerprint characteristic points when the humidity level is high may be longer than when the humidity level is low. The similarity extraction unit 140 may acquire information on the difference in the number of the plurality of fingerprint feature points according to the humidity level or the difference in the distance between the plurality of fingerprint feature points for each of the plurality of fingerprint information in advance, The minimum value having the reliability of the first degree of similarity can be calculated according to the humidity level, and the calculated minimum value can be set as the first threshold value.

In addition, the similarity extraction unit 140 may calculate a signal-to-noise ratio (SNR) of each of a plurality of electrocardiogram signals according to a humidity level, and extract a second threshold value using a signal-to-noise ratio. The similarity extraction unit 140 may calculate the intensity of a signal according to a humidity level of a plurality of electrocardiogram signals stored in advance. The similarity extraction unit 140 may store a noise value corresponding to a humidity level of a plurality of electrocardiogram signals in advance and may use a noise value according to a humidity level of a plurality of electrocardiogram signals and a strength of a signal to calculate a plurality of electrocardiogram The signal-to-noise ratio of each signal can be calculated. For example, the intensity of the plurality of electrocardiogram signals when the humidity level is high may be greater than the intensity of the plurality of electrocardiogram signals when the humidity level is low. Accordingly, the signal-to-noise ratio of a plurality of electrocardiogram signals when the humidity level is high may be larger than the signal-to-noise ratio of a plurality of electrocardiogram signals when the humidity level is low. The similarity-level extracting unit 140 may statistically analyze the signal-to-noise ratio of each of a plurality of electrocardiogram signals according to a humidity level, calculate a minimum value having reliability of the second similarity level according to the humidity level, Can be set to a second threshold value.

In one embodiment, the similarity extraction unit 140 may set the first weight and the second weight such that the first weight has a negative correlation with the humidity level and the second weight has a positive correlation with the humidity level have. This is because the higher the humidity level, the lower the quality of the fingerprint information and the higher the quality of the ECG waveform. Accordingly, the similarity extraction unit 140 reflects the first degree of similarity more than the second degree of similarity in the degree of similarity as the quality of the fingerprint information increases, and reflects the second degree of similarity more than the first degree of similarity as the quality of the electrocardiogram waveform increases . The similarity extraction unit 140 may set the first weight and the second weight so that the sum of the first weight and the second weight is constant irrespective of the humidity level. For example, the similarity extraction unit 140 may set the first weight and the second weight such that the sum of the first weight and the second weight is 1.

The authentication unit 150 can authenticate whether the user is a user registered in advance using the mixed similarity degree. The authentication unit 150 can authenticate a user as a previously registered user when the degree of hybrid similarity is greater than a predetermined threshold value and can authenticate the user as a user who has not been registered in advance when the degree of hybrid similarity is less than a predetermined threshold value can do. In one embodiment, the authentication unit 150 may arbitrarily set the critical mixture value, or may set the critical mixture value under the control of the external apparatus.

When the user is authenticated as a user registered in advance, the authentication device 110 can grant the user access right to the device having the authentication device 110. When the user is authenticated as a user who has not been registered in advance, the authentication device 110 may deny access to the device on which the user's authentication device 110 is mounted. As described above, the authentication apparatus 110 can authenticate whether or not the user is a registered user in a robust and accurate manner with respect to the humidity level of the skin of the user, by performing the authentication of the user using the mixed similarity degree.

2 is a diagram for explaining quality of fingerprint information and electrocardiographic waveform according to a humidity level according to an embodiment.

Referring to FIG. 2, the fingerprint information acquired by the authentication device and the quality of the electrocardiogram waveform may vary depending on the humidity level. In the example of FIG. 2, when the humidity level at the finger touching the fingerprint sensor is low (for example, 10%), the authentication device can extract 26 fingerprint feature points as in the fingerprint information 211. Further, when the humidity level at the finger touching the fingerprint sensor is high (for example, 80%), the authentication device extracts thirteen fingerprint feature points, which are half the humidity level is low can do.

Further, in the example of Fig. 2, the signal-to-noise ratio of the electrocardiogram signal may be lowered when the humidity level at the finger touching the fingerprint sensor is low (for example, 10%), An electrocardiogram waveform can be obtained. Further, when the humidity level in the finger touching the fingerprint sensor is high (for example, 80%), the signal-to-noise ratio of the electrocardiogram signal can be increased, and accordingly, the authentication device can acquire a high-quality electrocardiogram have. This may be due to the fact that the microcurrent between the electrodes of the ECG sensor and the skin of the user can flow more easily due to the moisture of the user's skin contacting the ECG sensor.

In this way, in consideration of the characteristic that the quality of the fingerprint information and the electrocardiogram waveform is varied by the humidity level, the authentication device calculates the first degree of similarity indicating the degree of similarity between the reference fingerprint information and the user's fingerprint information and the first degree of similarity between the reference ECG waveform and the user's ECG waveform The second degree of similarity representing the degree of similarity may be adaptively adjusted based on the humidity level so that the user can extract the mixed similarity degree indicating whether or not the user matches the pre-registered user corresponding to the reference fingerprint information and the reference ECG waveform, To authenticate whether the user is a user registered in advance.

FIG. 3 is a diagram for explaining threshold values of a first similarity degree and a second similarity degree according to a humidity level according to an embodiment.

Referring to FIG. 3, the graph 310 may represent a first threshold 320, which is a first similarity threshold, and a second threshold 330, which is a threshold of a second similarity. Here, the first degree of similarity may indicate the degree of similarity between the reference fingerprint information and the fingerprint information of the user who tries to authenticate, and the second degree of similarity may indicate the degree of similarity between the reference ECG waveform and the ECG waveform of the user attempting authentication. The horizontal axis of the graph 310 represents the humidity level, and the vertical axis represents the level of the first threshold 320 and the second threshold 330, respectively.

The quality of the fingerprint information and electrocardiogram waveform can be varied by the humidity level. For example, the higher the humidity level, the lower the quality of the fingerprint information and the higher the quality of the electrocardiographic waveform. Using this fingerprint information and the characteristics of the electrocardiogram waveform, the authentication device can set the first threshold value 320 and the second threshold value 330.

In one embodiment, the authentication apparatus can acquire information on the difference in the number of the plurality of fingerprint feature points according to the humidity level or the difference in the distance between the plurality of fingerprint feature points, for each of the plurality of fingerprint information pieces stored in advance, The information may be statistically analyzed to calculate a minimum value with which the first degree of similarity is reliable according to the humidity level and set the calculated minimum value to the first threshold value 320. [

Also, the authentication apparatus calculates the signal-to-noise ratio of each of the plurality of electrocardiogram signals according to the humidity level, statistically analyzes the signal-to-noise ratio of each of the plurality of electrocardiogram signals according to the humidity level, And the calculated minimum value can be set to the second threshold value 330. In this case,

In another embodiment, the authentication device may pre-store information about a first threshold and a second threshold, such as graph 310. For example, the authentication apparatus may previously calculate information on the first threshold value 320 and the second threshold value 330 according to the humidity level and store the information in the lookup table. Alternatively, the authentication apparatus may calculate the lookup table or the lookup table May be received from an external device. The authentication apparatus can set the first threshold value 320 and the second threshold value 330 by referring to the lookup table.

The authentication apparatus applies a first threshold value 320, a second threshold value 330, a first weight value, and a second weight value to the first similarity degree and the second similarity degree to extract a mixing threshold value, The user can be authenticated.

In one embodiment, the authentication device may calculate the mixing threshold using Equation (1) described above. For example, assuming that the humidity level 341 is 30% and the first threshold value 321 is 80%, assuming that the highest level of the humidity level is 100%, the lowest level is 0%, and the critical mixture value is 10, The second threshold value 331 is 40, the first weight value is 0.8, and the second weight value is 0.2. At this time, when the first degree of similarity is 90 and the second degree of similarity is 30, the degree of mixture similarity can be calculated to be 8. In this case, the degree of mixture similarity is smaller than the threshold mixed value, whereby the authentication device can authenticate the user as a user who has not been registered in advance, and can block access to the device provided with the authentication device of the user. As another example, under the same assumption as in the above example, when the humidity level 342 is 70%, the first threshold 322 is 20, the second threshold 332 is 60, the first weight is 0.2 , And the second weight may be 0.8. At this time, if the first degree of similarity is 30 and the second degree of similarity is 70, the degree of similarity of the mixture can be calculated to be 10. In this case, the degree of mixture similarity is larger than the threshold mixture value, whereby the authentication apparatus can authenticate the user as a predetermined user, and can allow access to the apparatus having the authentication apparatus of the user.

4 is a view for explaining a lookup table including information according to a humidity level according to an embodiment.

Referring to FIG. 4, the lookup table 410 may include information on a first threshold 420, a second threshold 430, a first weight 440, and a second weight 450.

Here, the first threshold value 420 represents a minimum value with which the first similarity degree indicating the degree of similarity between the reference fingerprint information and the fingerprint information of the user who tries to authenticate is reliable, and the second threshold value 430 represents the reference ECG waveform And the second degree of similarity indicating the degree of similarity between the electrocardiogram waveform of the user who tries to authenticate may represent a minimum value having reliability. The first weight 440 represents a ratio reflecting the first degree of similarity to the calculation of the degree of similarity indicating whether or not the user coincides with the previously registered user and the second weight 450 indicates the second degree of similarity to the calculation of the degree of similarity Can be expressed.

The authentication apparatus may calculate the information about the first threshold value 420, the second threshold value 430, the first weight value 440 and the second weight value 450 in advance and store them in the lookup table 410, (A first threshold value, a second threshold value, a first weight value, and a second weight value according to each humidity level) of the lookup table 410 or the lookup table 410 using an interface . The authentication apparatus can set the first threshold value 420, the second threshold value 430, the first weight value 440 and the second weight value by referring to the entry value of the lookup table or the lookup table. Thus, the authentication apparatus can extract the first threshold value 420, the second threshold value 430, the first weight value 440, and the second weight value without performing an additional operation, The amount of computation performed by the apparatus to authenticate the user can be reduced, and the computation speed for performing authentication can be increased.

5 is a block diagram showing an authentication apparatus according to another embodiment.

5, the authentication device 510 may include a fingerprint sensor 520, an electrocardiogram sensor 530, a humidity sensor 540, and a processor 550.

The fingerprint sensor 520 can sense the fingerprint information of the user. In one embodiment, the fingerprint sensor 520 may include an optical sensor, a semiconductor device type sensor, an ultrasonic type sensor, a thermal sense type sensor, a non-contact type sensor or a hybrid type sensor.

The electrocardiogram sensor 530 may sense the electrocardiographic waveform of the user using the first electrode, the second electrode, and the third electrode. In one embodiment, the electrocardiograph sensor 530 may include first to third electrodes, an amplifier, and a digital converter. The first to third electrodes may be in contact with the skin of a user to sense a user's electrocardiogram signal. The amplifier can amplify the electrocardiogram signal sensed by the first to third electrodes. In one embodiment, the amplifier may be represented by an analog front end (AFE). Digital converter converts an amplified electrocardiogram signal into a digital signal to extract an electrocardiogram waveform. In addition, the electrocardiogram sensor 530 can remove the noise of the electrocardiogram waveform through a preprocessing process.

The humidity sensor 540 may sense the humidity level of the user's skin. In one embodiment, the humidity sensor 540 senses the amount of moisture evaporating from the user's skin and converts it to a humidity level.

In one embodiment, the first electrode of the electrocardiogram sensor 530, the fingerprint sensor 520 and the humidity sensor 540 may be located within a predetermined area within the authentication device 510. Accordingly, the electrocardiogram sensor 530, the fingerprint sensor 520, and the humidity sensor 540 can sense the user's one finger to acquire the electrocardiogram waveform, the fingerprint information, and the humidity level, respectively.

The processor 550 converts the first similarity degree indicating the degree of similarity between the fingerprint information acquired by the fingerprint sensor 520 and the reference fingerprint information and the second degree of similarity indicating the degree of similarity between the ECG waveform acquired by the ECG sensor 530 and the reference ECG waveform, Level to determine whether the user who has been sensed by the fingerprint sensor 520 and the electrocardiogram sensor 530, the reference fingerprint information, and the similarity degree indicating whether or not the previously registered users corresponding to the reference ECG waveforms match with each other are extracted can do. The processor 550 extracts a plurality of fingerprint feature points of the fingerprint information acquired by the fingerprint sensor 520 and generates a plurality of fingerprint feature points of the fingerprint information acquired by the fingerprint sensor 520 and a plurality of fingerprint feature points of the reference fingerprint information The first degree of similarity can be extracted. The processor 550 extracts a plurality of electrocardiographic feature points of the electrocardiogram waveform acquired by the electrocardiogram sensor 530 and acquires a plurality of electrocardiographic feature points of the electrocardiogram waveform acquired by the electrocardiogram sensor 530 and a plurality of electrocardiographic feature points The second degree of similarity can be extracted using the distance between the second degree of similarity.

The processor 550 extracts from the predetermined reference information a first threshold value indicating a minimum value for which the first degree of similarity is reliable and a second threshold value indicating a minimum value for which the second degree of similarity is reliable, The first threshold value and the second threshold value can be set in consideration of the fingerprint information and the relationship between the quality of the plurality of ECG waveforms stored in advance and the humidity level.

The processor 550 may also be configured such that the first weight has a negative correlation with the humidity level, the second weight has a positive correlation with the humidity level, and the sum of the first and second weights is independent of the humidity level The first weight and the second weight can be set to be constant.

The processor 550 may extract the mixture similarity by applying a first threshold value and a second threshold value that are determined by the humidity level to the first similarity degree and the second similarity degree. In addition, the processor 550 may extract the similarity degree by applying the first weight and the second weight together with the first threshold and the second threshold to the first similarity and the second similarity. For example, the processor 550 applies a first weight to the difference value between the first similarity and the first threshold value, applies a second weight to the difference value between the second similarity value and the second threshold value, Can be extracted.

The processor 550 may use the mixed similarity to authenticate whether the user is a pre-registered user. For example, the processor 550 may authenticate the user as a pre-registered user if the degree of mixture similarity is greater than a predetermined threshold value, and if the degree of mixture similarity is below a predetermined threshold value, You can authenticate as a user.

6 is a diagram for explaining an example of an authentication apparatus according to an embodiment.

Referring to FIG. 6, the mobile terminal 610 may include an electrocardiogram sensor, a fingerprint sensor 630, and a humidity sensor 640. The electrocardiograph sensor may include an anode electrode 621, a reference electrode 622, and a cathode electrode 623 for sensing electrocardiogram signals. The anode electrode 621 and the reference electrode 622 may be located on the side of the mobile terminal 610 and the cathode electrode 623, the fingerprint sensor 630 and the humidity sensor 630 may be located on the side of the mobile terminal 610. In one embodiment, And may be located at the lower end of the display unit 610.

When the user touches the skin with the anode electrode 621 and the reference electrode 622 and contacts the finger with the cathode electrode 623, the fingerprint sensor 630 and the humidity sensor 640, the fingerprint sensor 630, The sensor and humidity sensor 640 can sense the user's fingerprint information, ECG waveform, and humidity level, respectively. For example, the fingerprint sensor 630, the electrocardiogram sensor, and the humidity sensor 640 can sense the user's fingerprint information, electrocardiographic waveform, and humidity level from one finger of the user, respectively.

The mobile terminal 610 transmits a first degree of similarity indicating the degree of similarity between the fingerprint information acquired by the fingerprint sensor 630 and the reference fingerprint information and a second degree of similarity indicating the degree of similarity between the electrocardiogram waveform acquired by the electrocardiographic sensor and the reference ECG waveform, Based on the fingerprint sensor 630 and the electrocardiogram sensor, and the similarity degree indicating whether or not the user who has sensed the fingerprint sensor 630 and the electrocardiogram sensor match the reference fingerprint information and the previously registered user corresponding to the reference ECG waveform. The mobile terminal 610 applies the first weight to the difference value between the first similarity and the first threshold value and applies the second weight to the difference value between the second similarity value and the second threshold value to extract the mixed similarity . In this case, the mobile terminal 610 extracts a first threshold value, a second threshold value, a first weight value, and a second weight value from predetermined reference information, extracts a plurality of previously stored fingerprint information, and a quality of a plurality of previously stored ECG waveforms The first threshold value, the second threshold value, the first weight value, and the second weight value can be set in consideration of the relationship between the first threshold value and the humidity level.

The mobile terminal 610 may authenticate whether the user is a pre-registered user using the mixed similarity. For example, the mobile terminal 610 may authenticate the user as a pre-registered user and allow the user to access the mobile terminal 610 if the degree of hybridization is greater than a predetermined threshold value.

7 is a diagram for explaining an example of an authentication apparatus according to another embodiment.

7, the wearable terminal 710 may include an electrocardiogram sensor, a fingerprint sensor 731, and a humidity sensor 741. FIG.

The electrocardiograph sensor may include an anode electrode 722, a reference electrode 723, and a cathode electrode 721 for sensing an ECG signal. The anode electrode 722 and the reference electrode 723 may be located on the rear surface of the wearable terminal 710 and the cathode electrode 721, the fingerprint sensor 731 and the humidity sensor 741 may be located on the rear surface of the wearable terminal 710. [ (Not shown). When the user touches the skin of the wrist with the anode electrode 722 and the reference electrode 723 and contacts the finger with the cathode electrode 721, the fingerprint sensor 731 and the humidity sensor 741, the fingerprint sensor 731, The electrocardiogram sensor, and the humidity sensor 741 can sense the fingerprint information of the user, the electrocardiogram waveform, and the humidity level, respectively. For example, the fingerprint sensor 731, the electrocardiogram sensor, and the humidity sensor 741 can sense the user's fingerprint information, ECG waveform, and humidity level from the user's one finger, respectively.

Similar to the mobile terminal 610 of FIG. 6, the wearable terminal 710 stores the first degree of similarity indicating the degree of similarity between the fingerprint information and the reference fingerprint information acquired from the fingerprint sensor 731, the electrocardiogram waveform obtained from the fingerprint sensor 731, A second degree of similarity between the reference ECG waveforms is adaptively adjusted based on the humidity level to extract a mixed similarity degree indicating whether the user is in agreement with a previously registered user corresponding to the reference fingerprint information and the reference ECG waveform, It is possible to authenticate whether the user is a user registered in advance using the mixed similarity.

8 is a diagram for explaining an example of an authentication apparatus according to another embodiment.

8, the mobile terminal 810 may include an electrocardiogram sensor, a fingerprint sensor 830, and a humidity sensor 840. The electrocardiogram sensor may include an anode electrode 821, a reference electrode 822, and a cathode electrode 823 for sensing electrocardiogram signals. The anode electrode 821 and the reference electrode 822 may be located on the side of the mobile terminal 810 and the cathode electrode 823, the fingerprint sensor 830 and the humidity sensor 830 may be located on the side of the mobile terminal 810. In one embodiment, (Not shown).

The mobile terminal 810 can obtain fingerprint information of the user registered in advance from the server 850, reference fingerprint information indicating the electrocardiogram waveform, and information on the reference electrocardiogram waveform. The mobile terminal 810 displays a first degree of similarity between the fingerprint information acquired by the fingerprint sensor 830 and the reference fingerprint information and a second degree of similarity between the electrocardiogram waveform acquired by the electrocardiograph sensor and the reference electrocardiogram waveform, The first threshold value, the second threshold value, the first weight value, and the second weight value, which are determined by the first threshold value, the first threshold value, the second threshold value, the first weight value, and the second weight value. In one embodiment, the mobile terminal 810 may transmit to the server 850 the humidity level obtained at the humidity sensor 840. The server 850 may extract a first threshold value, a second threshold value, a first weight value, and a second weight value from predetermined reference information based on the humidity level received from the mobile terminal 810 according to the humidity level, The first threshold value, the second threshold value, the first weight value, and the second weight value can be set in consideration of the fingerprint information and the relationship between the quality of the plurality of electrocardiographic waveforms stored in advance and the humidity level, A first weight, and a second weight to the mobile terminal 810. The mobile terminal 810 may send a first threshold, a second threshold, a first weight, and a second weight, which are received from the server 850, The weights can be applied to the first similarity degree and the second similarity degree to extract the mixed similarity degree.

The mobile terminal 810 may authenticate whether the user is a pre-registered user using the mixed similarity. For example, the mobile terminal 810 may authenticate the user as a pre-registered user if the degree of hybridization is greater than a predetermined threshold mixed value, and may transmit authentication information to the server 850 that the user is a pre-registered user .

In one embodiment, the server 850 may transmit the lookup table 410 described in FIG. 4 to the mobile terminal 810 and may store the entry value of the lookup table 410 (the first threshold value according to the humidity level, A threshold, a first weight, and a second weight). In this case, the mobile terminal 810 refers to the entry value of the look-up table 410 or the lookup table 410 and obtains the first degree of similarity from the predetermined reference information based on the humidity level acquired by the humidity sensor 840, The similarity, the first weight, and the second weight. The mobile terminal 810 may extract the similarity degree by applying the extracted first similarity, second similarity, first weight, and second weight. The server 850 may allow the user to access the server 850 using the authentication information received from the mobile terminal 810.

9 is a flowchart illustrating an authentication method according to an embodiment.

Referring to FIG. 9, the authentication device may acquire the fingerprint information of the user and the electrocardiogram waveform (910).

In addition, the authentication device may acquire a humidity level of the user's skin (920).

Also, the authentication apparatus may calculate a first degree of similarity between the reference fingerprint information and the fingerprint information, and a second degree of similarity between the reference ECG waveform and the ECG waveform (930).

The authentication apparatus adaptively adjusts the first and second similarities based on the humidity level to extract a mixed similarity degree indicating whether the user is in agreement with a previously registered user corresponding to the reference fingerprint information and the reference ECG waveform (940).

In addition, the authentication apparatus can authenticate 950 whether the user is a pre-registered user using the degree of similarity.

The authentication method according to the embodiment shown in FIG. 9 can be applied to the authentication method illustrated in FIG. 1 through FIG. 8 as it is, so that a detailed description will be omitted.

10 is an operation flowchart showing an authentication method according to another embodiment.

Referring to FIG. 10, the authentication apparatus can acquire a plurality of biometric information of a user (1010.)

In addition, the authentication device may obtain the humidity level of the user's skin (1020).

Further, the authentication apparatus may calculate the individual similarity degree of each of the plurality of biometric information items, which represents the similarity between each of the plurality of biometric information items and the reference biometric information items corresponding to the plurality of biometric information items among the plurality of reference biometric information items (1030) .

The authentication apparatus adaptively adjusts the individual similarity degree of each of the plurality of biometric information on the basis of the humidity level so as to extract a mixed similarity degree indicating whether or not the user is in agreement with a previously registered user corresponding to the plurality of biometric information (1040).

In addition, the authentication device may authenticate 1050 whether the user is a pre-registered user using the degree of similarity.

The authentication method according to another embodiment shown in FIG. 10 may be applied to the authentication method illustrated in FIG. 1 through FIG. 8 as it is, so that a detailed description will be omitted.

The apparatus described above may be implemented as a hardware component, a software component, and / or a combination of hardware components and software components. For example, the apparatus and components described in the embodiments may be implemented within a computer system, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA) A programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For ease of understanding, the processing apparatus may be described as being used singly, but those skilled in the art will recognize that the processing apparatus may have a plurality of processing elements and / As shown in FIG. For example, the processing device may comprise a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded. The software and / or data may be in the form of any type of machine, component, physical device, virtual equipment, computer storage media, or device , Or may be permanently or temporarily embodied in a transmitted signal wave. The software may be distributed over a networked computer system and stored or executed in a distributed manner. The software and data may be stored on one or more computer readable recording media.

The method according to an embodiment may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions to be recorded on the medium may be those specially designed and configured for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (24)

  1. A biometric information acquiring unit for acquiring the fingerprint information of the user and the electrocardiogram waveform;
    A humidity level obtaining unit for obtaining a humidity level of the skin of the user;
    A first degree of similarity between the reference fingerprint information and the fingerprint information and a second degree of similarity between the reference ECG waveform and the ECG waveform, A degree of similarity extracting unit for extracting a degree of similarity indicating whether or not the user matches a pre-registered user corresponding to the electrocardiogram waveform; And
    An authentication unit for authenticating whether the user is the pre-registered user using the mixed similarity,
    / RTI >
    Authentication device.
  2. The method according to claim 1,
    Wherein the biometric information obtaining unit
    A fingerprint feature point extracting unit for sensing the fingerprint information using a fingerprint sensor and extracting a plurality of fingerprint feature points of the fingerprint information; And
    An electrocardiogram feature point extracting unit for extracting the electrocardiogram waveform using an electrocardiogram sensor and extracting a plurality of electrocardiogram feature points of the electrocardiogram waveform,
    / RTI >
    Authentication device.
  3. 3. The method of claim 2,
    The electrocardiogram sensor includes:
    A plurality of electrodes for acquiring the electrocardiogram signal of the user;
    An amplifier for amplifying the electrocardiogram signal; And
    A digital converter for converting the amplified electrocardiogram signal into a digital signal and extracting the electrocardiogram waveform;
    / RTI >
    Authentication device.
  4. 3. The method of claim 2,
    Wherein the fingerprint information, the electrocardiographic waveform,
    And obtaining from the same finger of the user,
    Authentication device.
  5. 3. The method of claim 2,
    Wherein the similarity-
    Extracting the mixed similarity using the difference value between the first similarity degree and the first threshold value determined by the humidity level and the difference value between the second similarity degree and the second threshold value determined by the humidity level ,
    Authentication device.
  6. 6. The method of claim 5,
    Wherein the similarity-
    Extracting the first threshold value and the second threshold value from predetermined reference information,
    Authentication device.
  7. 6. The method of claim 5,
    Wherein the similarity-
    Using a difference in the number of the plurality of fingerprint feature points of each of a plurality of fingerprint information previously stored according to the humidity level or a difference in distance between a plurality of fingerprint feature points of each of the plurality of fingerprint information according to the humidity level, Lt; / RTI >
    Authentication device.
  8. 6. The method of claim 5,
    Wherein the similarity-
    Calculating a signal-to-noise ratio (SNR) of each of a plurality of electrocardiogram signals stored in advance according to the humidity level, and extracting the second threshold value using the SNR,
    Authentication device.
  9. 6. The method of claim 5,
    Wherein the similarity-
    Applying a first weight determined by the humidity level to a difference between the first similarity and the first threshold and determining a difference between the second similarity and the second threshold by the humidity level And extracting the similarity degree by applying a second weight to the second weight,
    Authentication device.
  10. 10. The method of claim 9,
    Wherein the similarity-
    Calculating the similarity degree by summing a difference value between the first similarity degree and the first threshold value, to which the first weight is applied, and a difference value between the second similarity degree and the second threshold value to which the second weight is applied,
    Authentication device.
  11. 10. The method of claim 9,
    Wherein the similarity-
    Wherein the first weight has a negative correlation with the humidity level and the second weight has a positive correlation with the humidity level and wherein the sum of the first weight and the second weight is independent of the humidity level Setting the first weight and the second weight to be constant,
    Authentication device.
  12. The method according to claim 1,
    Wherein,
    Authenticating the user as the pre-registered user if the degree of mixture similarity is greater than a predetermined threshold value,
    Authentication device.
  13. 3. The method of claim 2,
    Wherein the plurality of fingerprint feature points comprise:
    Wherein the fingerprint information includes at least two of a ridge, an upper center point, a lower center point, a left delta delta, a right delta delta,
    Authentication device.
  14. 3. The method of claim 2,
    Wherein the plurality of ECG feature points include:
    A PR segment, a QRS complex, an ST segment, a T wave, a U wave, a PR interval or a QT interval QT of the ECG waveform interval < / RTI >
    Authentication device.
  15. A fingerprint sensor for sensing fingerprint information of a user;
    An electrocardiogram sensor for sensing the electrocardiogram waveform of the user using the first electrode, the second electrode, and the third electrode;
    A humidity sensor for sensing the humidity level of the user's skin; And
    A first degree of similarity between the reference fingerprint information and the fingerprint information and a second degree of similarity between the reference ECG waveform and the ECG waveform, A processor for extracting a mixed similarity degree indicating whether or not the user is in agreement with a pre-registered user corresponding to the electrocardiogram waveform and authenticating whether the user is the pre-registered user using the mixed similarity degree,
    / RTI >
    Authentication device.
  16. 16. The method of claim 15,
    The first electrode, the fingerprint sensor, and the humidity sensor,
    And which is located within a predetermined area,
    Authentication device.
  17. 16. The method of claim 15,
    The first electrode, the fingerprint sensor, and the humidity sensor,
    Sensing the same finger of the user,
    Authentication device.
  18. 16. The method of claim 15,
    The processor comprising:
    Extracting the mixed similarity using the difference value between the first similarity degree and the first threshold value determined by the humidity level and the difference value between the second similarity degree and the second threshold value determined by the humidity level ,
    Authentication device.
  19. 19. The method of claim 18,
    The processor comprising:
    Applying a first weight determined by the humidity level to a difference between the first similarity and the first threshold and determining a difference between the second similarity and the second threshold by the humidity level And extracting the similarity degree by applying a second weight to the second weight,
    Authentication device.
  20. 20. The method of claim 19,
    The processor comprising:
    Calculating the similarity degree by summing a difference value between the first similarity degree and the first threshold value, to which the first weight is applied, and a difference value between the second similarity degree and the second threshold value to which the second weight is applied,
    Authentication device.
  21. A biometric information obtaining unit for obtaining a plurality of biometric information of a user;
    A humidity level obtaining unit for obtaining a humidity level of the skin of the user;
    The individual similarity degree indicating the degree of similarity between each of the plurality of pieces of the biometric information and the reference biometric information corresponding to each of the plurality of pieces of the biometric information among the plurality of pieces of the reference biometric information is adaptively adjusted based on the humidity level, A degree of similarity extracting unit for extracting a degree of similarity indicating whether or not the user matches a user registered in advance corresponding to the information; And
    An authentication unit for authenticating whether the user is the pre-registered user using the mixed similarity,
    / RTI >
    Authentication device.
  22. Acquiring the fingerprint information of the user and the electrocardiogram waveform;
    Obtaining a humidity level of the skin of the user;
    Calculating a first degree of similarity between the reference fingerprint information and the fingerprint information and a second degree of similarity between the reference ECG waveform and the ECG waveform;
    Wherein the first degree of similarity and the second degree of similarity are adaptively adjusted based on the humidity level to determine a degree of similarity indicating whether or not the user is in agreement with a previously registered user corresponding to the reference fingerprint information and the reference ECG waveform Extracting; And
    Authenticating whether the user is the pre-registered user using the mixed similarity degree
    / RTI >
    Authentication method.
  23. Acquiring a plurality of biometric information of a user;
    Obtaining a humidity level of the skin of the user;
    Calculating individual degree of similarity of each of the plurality of pieces of biometric information and each of the plurality of pieces of biometric information indicating a degree of similarity between reference biometric information corresponding to each of the plurality of pieces of biometric information among a plurality of pieces of reference biometric information;
    Extracting a mixed similarity degree indicating whether or not the user is in agreement with a previously registered user corresponding to the plurality of biometric information by adaptively adjusting an individual similarity degree of each of the plurality of biometric information on the basis of the humidity level; And
    Authenticating whether the user is the pre-registered user using the mixed similarity degree
    / RTI >
    Authentication method.
  24. A computer-readable recording medium having recorded thereon a program for performing the method of any one of claims 22 and 23.
KR1020140101660A 2014-08-07 2014-08-07 Method and apparatus for authenticating user using fingerprint and ecg signal KR20160017941A (en)

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Application Number Priority Date Filing Date Title
KR1020140101660A KR20160017941A (en) 2014-08-07 2014-08-07 Method and apparatus for authenticating user using fingerprint and ecg signal

Applications Claiming Priority (5)

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KR1020140101660A KR20160017941A (en) 2014-08-07 2014-08-07 Method and apparatus for authenticating user using fingerprint and ecg signal
CN201510122310.5A CN106031638B (en) 2014-08-07 2015-03-19 User authentication method and equipment based on fingerprint and ECG signal
US14/666,522 US9576179B2 (en) 2014-08-07 2015-03-24 User authentication method and apparatus based on fingerprint and electrocardiogram (ECG) signal
EP15179682.8A EP2983109A3 (en) 2014-08-07 2015-08-04 User authentication method and apparatus based on fingerprint and electrocardiogram (ECG) signal
JP2015154910A JP6553976B2 (en) 2014-08-07 2015-08-05 Authentication apparatus, authentication method and recording medium

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KR20160017941A true KR20160017941A (en) 2016-02-17

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20180137771A (en) * 2017-06-19 2018-12-28 한국인터넷진흥원 User identification apparatus based on multi-modal using bio-signal and method thereof

Families Citing this family (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20160136013A (en) * 2015-05-19 2016-11-29 엘지전자 주식회사 Mobile terminal and method for controlling the same
US9928398B2 (en) * 2015-08-17 2018-03-27 Invensense, Inc. Always-on sensor device for human touch
US20170124256A1 (en) * 2015-10-30 2017-05-04 General Electric Company Method and system for analyzing electrocardiograph data
KR20170073927A (en) * 2015-12-21 2017-06-29 삼성전자주식회사 Method and device for authenticating user
SE1650126A1 (en) * 2016-02-02 2017-08-03 Fingerprint Cards Ab Method and fingerprint sensing system for analyzing biometric measurements of a user
SE1650416A1 (en) * 2016-03-31 2017-10-01 Fingerprint Cards Ab Secure storage of fingerprint related elements
WO2017214582A1 (en) * 2016-06-09 2017-12-14 InSyte Systems Integrated light emitting display and sensors for detecting biologic characteristics
US20170337412A1 (en) * 2016-05-23 2017-11-23 InSyte Systems Light emitter and sensors for detecting biologic characteristics
CN106203303B (en) * 2016-06-30 2018-02-02 北京小米移动软件有限公司 Fingerprint identification device and method
CN106503525A (en) * 2016-10-31 2017-03-15 三星电子(中国)研发中心 Unlocked by fingerprint method, device and terminal
US10528714B2 (en) 2017-01-11 2020-01-07 Samsung Electronics Co., Ltd. Method and apparatus for authenticating user using electrocardiogram signal
US20180225495A1 (en) * 2017-02-06 2018-08-09 Fingerprint Cards Ab Method for authenticating a finger of a user of an electronic device
WO2018152711A1 (en) * 2017-02-22 2018-08-30 清华大学深圳研究生院 Electrocardiographic authentication-based door control system and authentication method therefor
EP3444746A4 (en) * 2017-07-05 2019-02-20 Shenzhen Goodix Technology Co., Ltd. Method, device, chip and terminal device for fingerprint collection
US20200033969A1 (en) * 2018-07-30 2020-01-30 Texas Instruments Incorporated Using driven shield and touch elements lock algorithm for achieving liquid tolerant capacitive touch solution

Family Cites Families (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5559504A (en) 1993-01-08 1996-09-24 Kabushiki Kaisha Toshiba Surface shape sensor, identification device using this sensor, and protected system using this device
US6026321A (en) 1997-04-02 2000-02-15 Suzuki Motor Corporation Apparatus and system for measuring electrical potential variations in human body
WO2001059733A2 (en) * 2000-02-14 2001-08-16 Pacific Consultants, Llc Security control method and system
WO2004012388A1 (en) 2002-07-29 2004-02-05 C-Signature Ltd. Method and apparatus for electro-biometric identiy recognition
EP1671257A1 (en) * 2003-09-30 2006-06-21 Philips Electronics N.V. System and method for adaptively setting biometric measurement thresholds
US8918900B2 (en) 2004-04-26 2014-12-23 Ivi Holdings Ltd. Smart card for passport, electronic passport, and method, system, and apparatus for authenticating person holding smart card or electronic passport
KR20060038119A (en) 2004-10-29 2006-05-03 에스케이 텔레콤주식회사 System for individual identification of medical network using bio-metrics and method thereof
EP1880254A4 (en) * 2005-03-17 2012-08-01 Imageware Systems Inc Multimodal biometric analysis
EP1924976A2 (en) 2005-08-18 2008-05-28 IVI Smart Technologies Inc. Biometric identity verification system and method
US20100045705A1 (en) 2006-03-30 2010-02-25 Roel Vertegaal Interaction techniques for flexible displays
JP2008077269A (en) 2006-09-20 2008-04-03 Fujitsu Fsas Inc Secure system and data protection method for data processor
KR101030311B1 (en) 2007-02-27 2011-05-23 (주)엠디앤유 Mobile Wearable Vital Sign Multi-Sensing Device and Physiological Status Activated Nomadic System
KR20110002373A (en) 2009-07-01 2011-01-07 주식회사 슈프리마 Fingerprint authentication apparatus with bio signal detector, and method thereof
CN101773394B (en) * 2010-01-06 2011-09-07 中国航天员科研训练中心 Identification method and identification system using identification method
US8598980B2 (en) 2010-07-19 2013-12-03 Lockheed Martin Corporation Biometrics with mental/physical state determination methods and systems
KR101203669B1 (en) 2010-10-25 2012-11-21 경희대학교 산학협력단 walking assisting device having user recognition function
US9646261B2 (en) 2011-05-10 2017-05-09 Nymi Inc. Enabling continuous or instantaneous identity recognition of a large group of people based on physiological biometric signals obtained from members of a small group of people
KR101270954B1 (en) 2011-05-24 2013-06-11 가톨릭대학교 산학협력단 Biometric system using ecg signal and fingerprint identification
KR101883964B1 (en) 2011-11-21 2018-08-31 엘지전자 주식회사 Terminal and control method thereof
CN202694091U (en) * 2012-04-12 2013-01-23 北京仁佳科技有限公司 Novel RFID identity identification electric power tool cabinet and safety tool intelligent management system

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20180137771A (en) * 2017-06-19 2018-12-28 한국인터넷진흥원 User identification apparatus based on multi-modal using bio-signal and method thereof

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